1. Field of Invention
The present invention relates to the field of ultrasound imaging. More specifically, it relates to detecting the depths of inter-tissue boundaries within an ultrasound image.
2. Description of Related Art
Ultrasound imaging refers to the imaging of structures below a subject's surface (such as the imaging of internal human organs below a skin surface) by the sending of sound waves of known frequency into the interior of the subject and observing any sound waves that bounce back. By monitoring how long it takes for sound waves to bounce back from an internal structure, it is possible to estimate the depth and shape of the structure within the subject. It is also possible to discern some characteristics about the internal structure based on how the sound waves are absorbed, dispersed or deflected.
Ultrasonography, or diagnostic sonography, refers to the use of ultrasound imaging techniques for imaging subcutaneous body structures, or tissues, for diagnostic purposes. Ultrasound imaging may be used to image various types of tissues, such as muscle, fat, tendons, vessels, internal organs, etc. Another example is obstetric sonography, which is used to image a developing baby during pregnancy.
Ultrasound imaging typically applies a series of ultrasound waves at a frequency above the human audible range, and observed the sound waves that bounce back. Each sound wave is observed separately and constitutes a scan signal, or a scan line of an image. The collection of observed sound waves, or scan lines or scan signals, are placed sequentially next to each other to construct a two-dimensional image in a manner similar to how images are created in a cathode ray tube.
A problem with ultrasound images is that they are typically very noisy, due in part to the great many tissues and fluids of differing densities and types encountered by a sound wave as it propagates and dissipates through its downward and upward paths through an observed body.
Another problem with ultrasound images is that they are constructed by moving an ultrasound wand over the surface of a target tissue area, but the resultant ultrasound image formed from one pass of the ultrasound wand is typically very narrow. This provides a user (i.e., an ultrasound technician) with only a small observable part (or swatch or slice) of the whole of the target tissue area. As a result, multiple swatches are typically needed to gather enough imaging information to span the whole of the target area. That is, a technician must make multiple passes with the ultrasound wand along different paths, store the image information from each pass, and try to put together the image information from the different passes.
The ability to stitch together multiple ultrasound images from multiple passes to create one larger ultra sound image is therefore beneficial. To stitch images together refers to the combining of image information from two or more images as seamlessly as possible/practical.
There are several examples of stitching ultrasound images. One example is found in European patent EP1531730A1 to Chin et al, which describes the stitching of multiple ultrasound images to construct a composite whole to aid in the diagnosis of breast cancer. Another example is provided in “Rapid Image Stitching and Computer-Aided Detection for Multipass Automated Breast Ultrasound”, Med. Phys. 37 (5), May 2010, by Chang et al., which describes using the sum of absolute block-mean difference (SBMD) measure to stitch ultrasound images.
In general, image stitching requires two more adjacent images having some overlapping portion. Characteristic features of each image (at least within their overlapping portions) are identified and described. The distinctive descriptions of the characteristic features in one image are then compared with those of its adjacent image to identify characteristic features that may correspond to each other (and thus correspond to the same point on an imaged scene). Characteristic features that correspond to each other may be said to be “indexed” or “correlated” to each other. In this manner, an index of corresponding (i.e. matched or correlated) characteristic features in the overlapping portions can be established. This indexing is then used to align and stitch together the two images.
After one has a good ultrasound image (either a singular ultrasound image or a composite of multiple stitched ultrasound images), the next task is to discern medical information from the dark, noisy image. On important piece of information that often needs to be extracted from ultrasound images is to the boundary depth (or boundary line) of different tissue types. Since an ultrasound image typically provides only a small view (or swatch), a full object will likely not be imaged since it would not fit within the swatch. Nonetheless, boundary localization of objects (or of different types of tissues) within an ultrasound image is important since they determination of the boundary depths (i.e. the depth at which a boundary line dividing two different tissue types is found). The boundary depths are useful in the measuring of object, or tissue, layers, such as for fat and/or muscle measurements. Being able to accurately measure fat/muscle layers is important for obesity control, fitness, and other health-related diagnoses.
Identifying these boundary lines, however, is challenging due to ultrasound images being highly noisy. Further complicating matters is that fat and muscle boundaries can be at various depths across different people. The identification of boundary lines is further complicated due to the shapes and image texture of fat and muscle boundaries both being highly variable.
Therefore, determination of boundary lines is typically left to well-trained technicians with much experience in this field. However, it would be helpful if the localization of tissue boundaries within an ultrasound image could be automated to reduce reliance on specialized technicians.
It is therefore an object of the present invention to provide a method to automatically identify tissue boundary lines within an ultrasound image.
It is a second object of the present invention to provide a method to automatically identify multiple boundaries lines of irregular shapes within an ultrasound image.
It a further object of the present invention to be able to identify boundary lines that delineate the boundary between fatty tissues and muscle tissues.